Ultra‐high spatial resolution BOLD fMRI in humans using combined segmented‐accelerated VFA‐FLEET with a recursive RF pulse design

Abstract

To alleviate the spatial encoding limitations of single-shot EPI by developing multi-shot segmented EPI for ultra-high-resolution fMRI with reduced ghosting artifacts from subject motion and respiration. Methods Segmented EPI can reduce readout duration and reduce acceleration factors, however, the time elapsed between segment acquisitions (on the order of seconds) can result in intermittent ghosting, limiting its use for fMRI. Here, "FLEET" segment ordering-where segments are looped over before slices-was combined with a variable flip angle progression (VFA-FLEET) to improve inter-segment fidelity and maximize signal for fMRI. Scaling a sinc pulse's flip angle for each segment (VFA-FLEET-Sinc) produced inconsistent slice profiles and ghosting, therefore, a recursive Shinnar-Le Roux (SLR) RF pulse design was developed (VFA-FLEET-SLR) to generate unique pulses for every segment that together produce consistent slice profiles and signals. Results The temporal stability of VFA-FLEET-SLR was compared against conventionalsegmented EPI and VFA-FLEET-Sinc at 3 T and 7 T. VFA-FLEET-SLR showed reductions in both intermittent and stable ghosting compared to conventional-segmented and VFA-FLEET-Sinc, resulting in improved image quality with a minor trade-off in temporal SNR. Combining VFA-FLEET-SLR with acceleration, we achieved a 0.6-mm isotropic acquisition at 7 T-without zoomed imaging or partial Fourier-demonstrating reliable detection of BOLD responses to a visual stimulus. To counteract the increased repetition time from segmentation, simultaneous multi-slice VFA-FLEET-SLR was demonstrated using RF-encoded controlled aliasing. Conclusions 3 VFA-FLEET with a recursive RF pulse design supports acquisitions with low levels of artifact and spatial blur, enabling fMRI at previously inaccessible spatial resolutions with a "fullbrain" field of view.

Motion‐insensitive susceptibility weighted imaging

“…Another possibility is that the mismatch is an effect of the nonrectangular slice profile, accumulating an error over the course of the VFA train. 24 Deeper investigation of this issue, however, was considered to fall outside the scope of this work.…”

“…If this is due to imperfect ghost correction, improved algorithms could be used, or the problem could be avoided by prospectively updating the interleaved snapshot EPI once per slice rather than each shot, at the cost of increasing the prospective update interval from 0.05 seconds to 0.2 seconds. Another possibility is that the mismatch is an effect of the nonrectangular slice profile, accumulating an error over the course of the VFA train 24 . Deeper investigation of this issue, however, was considered to fall outside the scope of this work.…”

“…Our proposed solution is SWI based on 2D spoiled GRE interleaved snapshot EPI, which effectively averts motion‐induced phase discrepancies by greatly reducing the temporal footprint of the acquisition of each slice. Interleaved snapshot EPI has previously been used for T 1 ‐weighted and ‐weighted imaging, 17 functional MRI, 15,22,24 diffusion MRI, 25 and parallel imaging calibration, 18 but not for SWI, to the best of our knowledge. The present work demonstrates that interleaved snapshot EPI in combination with prospective motion correction (aided by dynamic ghost correction) yields sharp SWI in the presence of large continuous motion.…”

Scotopic Vision Is Selectively Processed in Thick-Type Columns in Human Extrastriate Cortex

“…Moreover, the visual activation during scotopic light conditions is consistent with the hypothesis that scotopic vision is preferentially processed in a magnocellular-dominated “stream.” In contrast, activation during mid-range photopic light levels supports the hypothesis that photopic vision relies on both magnocellular and parvocellular processing. More direct tests using higher spatial resolution neuroimaging techniques (e.g., see ( Berman et al. 2020 )) are required.…”

Mesoscopic in vivo human T2* dataset acquired using quantitative MRI at 7 Tesla

“…We have implemented our geometric approach within the LayNii software suite (Huber et al, 2021) and have made them publicly available (see Section 5). Our mesoscopic tools can, in principle, be used for any type of voxel-based 3D images, including high resolution fMRI, histology, and lightsheet microscopy images (Amunts et al, 2013;Berman et al, 2021;Hildebrand et al, 2019;Huber et al, 2020).…”